The unprecedented growth in the easy availability of photo-editing tools has endangered the power of digital images.An image was supposed to be worth more than a thousand words,but now this can be said only if it can be authenticated orthe integrity of the image can be proved to be intact. In thispaper, we propose a digital image forensic technique for JPEG images. It can detect any forgery in the image if the forged portion called a ghost image is having a compression quality different from that of the cover image. It is based on resaving the JPEG image at different JPEG qualities, and the detection of the forged portion is maximum when it is saved at the same JPEG quality as the cover image. Also, we can precisely predictthe JPEG quality of the cover image by analyzing the similarity using Structural Similarity Index Measure (SSIM) or the energyof the images. The first maxima in SSIM or the first minima inenergy correspond to the cover image JPEG quality. We created adataset for varying JPEG compression qualities of the ghost and the cover images and validated the scalability of the experimental results.We also, experimented with varied attack scenarios, e.g. high-quality ghost image embedded in low quality of cover image,low-quality ghost image embedded in high-quality of cover image,and ghost image and cover image both at the same quality.The proposed method is able to localize the tampered portions accurately even for forgeries as small as 10x10 sized pixel blocks.Our technique is also robust against other attack scenarios like copy-move forgery, inserting text into image, rescaling (zoom-out/zoom-in) ghost image and then pasting on cover image.
翻译:照片编辑工具的简单化史前所未有的增长危及了数字图像的力量。 图像本应价值超过一千字, 但现在只有能够认证, 或图像的完整性能够被证明完整。 在本文件中, 我们为 JPEG 图像提议了一个数字图像法学技术。 如果被称为鬼影的伪造部分的压缩质量与封面图像的质量不同, 它可以检测图像中的任何伪造。 它基于以不同 JPEEG 质量重保存 JPEG 图像, 而如果在与封面图像相同的 JPEG 质量下保存时, 伪造部分的检测是最大化的。 此外, 我们可以精确地预测封面图像的 JPEG 质量, 使用结构相似性指数(SSIM) 或图像的能量来分析相似性。 SSIM 的第一个最大或第一个能量缩放与封面的图像质量不同。 我们创建了一个数据集, 用于将 JPEGEG 的压缩质量和覆盖图像的升级, 并且验证实验结果的缩放性。 即便在 JPEG 图像的精度中, 也用精度的精度和高质量 图像的图像的缩化方法进行实验性 。